#import dataset
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd


dataset = pd.read_csv("/Users/Desktop/beathika treatment/Kimchi_dataset.csv")
dataset.columns

Index(['Date', 'Price', 'Total Volume', 'Total Boxes', 'Small Boxes',
       'Large Boxes', 'XLarge Boxes', 'Region'],
      dtype='object')

dataset

	Date	Price	Total Volume	Total Boxes	Small Boxes	Large Boxes	XLarge Boxes	Region
0	3/25/2018	1.71	2321.82	2006.46	1996.46	10.00	0.0	Seoul
1	3/18/2018	1.66	3154.45	2580.60	2577.27	3.33	0.0	Seoul
2	3/11/2018	1.68	2570.52	2209.29	2209.29	0.00	0.0	Seoul
3	3/4/2018	1.48	3851.30	3242.98	3239.65	3.33	0.0	Seoul
4	2/25/2018	1.56	5356.63	4007.48	4007.48	0.00	0.0	Seoul
...	...	...	...	...	...	...	...	...
643	2/4/2018	1.63	17074.83	13498.67	13066.82	431.85	0.0	Boryeong
644	1/28/2018	1.71	13888.04	9264.84	8940.04	324.80	0.0	Boryeong
645	1/21/2018	1.87	13766.76	9394.11	9351.80	42.31	0.0	Boryeong
646	1/14/2018	1.93	16205.22	10969.54	10919.54	50.00	0.0	Boryeong
647	1/7/2018	1.62	17489.58	12014.15	11988.14	26.01	0.0	Boryeong

648 rows × 8 columns

from pandas_profiling import ProfileReport

prof = ProfileReport(dataset)
prof